Sensor-based pain management systems and methods

ABSTRACT

This document discusses, among other things, systems and methods for managing pain of a subject. A system includes a first sensor circuit to sense a first signal indicative of a functional state of the subject, a second sensor circuit to sense a second signal different from the first signal, and a controller circuit. The controller circuit may determine an operating mode of the second sensor circuit according to the sensed first signal, trigger the second senor circuit to sense the second signal under the determined operating mode, and generate a pain score using at least the second signal sensed under the determined operating mode. The pain score may be output to a patient or used for closed-loop control of a pain therapy.

CLAIM OF PRIORITY

This application is a continuation of U.S. application Ser. No.16/034,304, filed Jul. 12, 2018, which claims the benefit of priorityunder 35 U.S.C. § 119(e) of U.S. Provisional Patent Application Ser. No.62/533,789, filed on Jul. 18, 2017, each of which is herein incorporatedby reference in its entirety.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is related to commonly assigned U.S. Provisional PatentApplication Ser. No. 62/445,075, entitled “PAIN MANAGEMENT BASED ONFUNCTIONAL MEASUREMENTS”, filed on Jan. 11, 2017, which is incorporatedby reference in their entirety.

TECHNICAL FIELD

This document relates generally to medical systems and more particularlyto systems, devices, and methods for pain management.

BACKGROUND

Pain is one of the most common and among the most personally compellingreasons for seeking medical attention, and consumes considerablehealthcare resources each year. The relation between etiology,underlying mechanisms and the specific symptoms and signs related topainful disorders is complex. Pain in an individual patient may beproduced by more than one mechanism.

Chronic pain, such as pain present most of the time for a period of sixmonths or longer during the prior year, is a highly pervasive complaintand consistently associated with psychological illness. Chronic pain mayoriginate with a trauma, injury or infection, or there may be an ongoingcause of pain. Chronic pain may also present in the absence of any pastinjury or evidence of body damage. Common chronic pain can includeheadache, low back pain, cancer pain, arthritis pain, neurogenic pain(pain resulting from damage to the peripheral nerves or to the centralnervous system), or psychogenic pain (pain not due to past disease orinjury or any visible sign of damage inside or outside the nervoussystem).

Chronic pain may be treated or alleviated using medications,acupuncture, surgery, and neuromodulation therapy, among others.Examples of neuromodulation include Spinal Cord Stimulation (SCS), DeepBrain Stimulation (DBS), Peripheral Nerve Stimulation (PNS), andFunctional Electrical Stimulation (FES). Implantable neuromodulationsystems have been applied to deliver such a therapy. An implantableneuromodulation system may include an implantable neurostimulator, alsoreferred to as an implantable pulse generator (IPG), which canelectrically stimulate tissue or nerve centers to treat nervous ormuscular disorders. In an example, an IPG can deliver electrical pulsesto a specific region in a patient's spinal cord, such as particularspinal nerve roots or nerve bundles, to create an analgesic effect thatmasks pain sensation.

SUMMARY

By way of example, chronic pain management may involve determiningappropriate treatment regimens such as SCS and evaluating therapyefficacy. Accurate pain assessment and characterization are desirablefor managing patients with chronic pain. Currently, pain assessmentgenerally relies on patient subjective report of pain symptoms,including severity, pattern, or duration of pain. Based on the patientreported pain sensation, a clinician may prescribe a pain therapy, suchas to program an electrostimulator for delivering a neuromodulationtherapy. However, the subjective description of pain sensation may beconstrained by patient cognitive abilities. The subjective paindescription may also be subject to intra-patient variation, such as dueto a progression of a chronic disease, or a change in general healthstatus or medication. Having a patient to report and describe each painepisode that he or she has experienced is not efficient, and may delayappropriate pain therapy. Additionally, for patients in an ambulatorysetting who lacks immediate access to medical assistance, manualadjustment of pain therapy by a clinician may not be feasible especiallyif immediate therapy titration is required.

Some sensors may sense patient response to pain and detect onset of apain episode or worsening of pain. Operating these sensors for paindetection and pain assessment, however, may consume a lot of power andrequire substantial computing resources, particularly when chronic painmonitoring and assessment is desired. In certain implementations, somesensors may be incorporated into an ambulatory monitor for ambulatoryand chronic pain monitoring. The ambulatory monitor usually has limitedbattery power, storage space, information processing power, andcommunication bandwidth. These constraints may affect the performance ofsensor-based ambulatory pain assessment. Additionally, patient pain maybe associated with a patient context, such as when a patient engages inphysical activities, or during a certain time of a day. Using thepatient context may lead to more efficient sensor usage and improvedpain monitoring and assessment. The present inventors have recognizedthat there remains a demand for apparatus and methods of ambulatorymonitoring, sensor-based pain assessment, and automated pain therapy.

This document discusses, among other things, systems, devices, andmethods for assessing pain of a subject. The system includes a firstsensor circuit to sense from the patient a first signal indicative of afunctional state of the patient, a second sensor circuit to sense asecond signal different from the first signal, and a controller circuit.The second signal may include a physiological signal or a functionalsignal. The controller circuit may determine an operating mode of thesecond sensor circuit using the sensed first signal, trigger the secondsenor circuit to sense the second signal under the determined operatingmode, and generate a pain score using at least the second signal sensedunder the determined operating mode. The pain score can be output to apatient or used for closed-loop control of a pain therapy.

Example 1 is a system for managing pain of a patient. The systemcomprises a first sensor circuit that may sense from the patient a firstsignal indicative of a functional state of the patient, a second sensorcircuit that may sense from the patient a second signal different fromthe first signal, and a controller circuit. The controller circuit maydetermine an operating mode of the second sensor circuit using thesensed first signal, trigger the second sensor circuit to sense thesecond signal under the determined operating mode, and generate a painscore using at least the second signal sensed under the determinedoperating mode. The system may output the pain score to a user or aprocess.

In Example 2, the subject matter of Example 1 optionally includes anelectrostimulator coupled to the controller circuit that may generateelectrostimulation energy to treat pain. The controller circuit maycontrol the electrostimulator to deliver a pain therapy and to controlthe electrostimulation energy generated by the electrostimulatoraccording to the pain score.

In Example 3, the subject matter of Example 2 optionally includes theelectrostimulator that may deliver at least one of: a spinal cordstimulation; a brain stimulation; or a peripheral nerve stimulation.

In Example 4, the subject matter of any one or more of Examples 1-3optionally includes the first sensor circuit that may be coupled to atleast one ambulatory sensor to sense the first signal. The ambulatorysensor may include at least one of: an accelerometer; a gyroscope; amagnetometer; a strain gauge; or a global positioning system sensor.

In Example 5, the subject matter of any one or more of Examples 1-4optionally includes the first signal that may include a physicalactivity signal. The controller circuit may trigger the second sensorcircuit to sense the second signal under a first operating mode if thephysical activity signal falls below an activity threshold, and triggerthe second sensor circuit to sense the second signal under a secondoperating mode different from the first operating mode if the physicalactivity signal exceeds the activity threshold.

In Example 6, the subject matter of any one or more of Examples 1-4optionally includes the first signal that may include a physicalactivity signal. The controller circuit may trigger the second sensorcircuit to sense the second signal under a first operating mode if thephysical activity signal corresponds to a physical activity templateindicative of a physical activity pattern when the patient is free ofpain, and trigger the second sensor circuit to sense the second signalunder a second operating mode different from the first operating mode ifthe physical activity signal fails to correspond to the physicalactivity template.

In Example 7, the subject matter of any one or more of Examples 1-3optionally includes the first signal that may include a posture signal.

In Example 8, the subject matter of any one or more of Examples 1-3optionally includes the first signal that may include a gait or abalance signal.

In Example 9, the subject matter of any one or more of Examples 1-3optionally includes the first signal that may include a range-of-motionsignal.

In Example 10, the subject matter of any one or more of Examples 1-9optionally includes the second signal that may include at least one of:a cardiac electrical activity signal; an electromyography signal; aphotoplethysmography signal; a galvanic skin response signal; anelectroencephalogram signal; or a hemodynamic signal.

In Example 11, the subject matter of any one or more of Examples 1-10optionally includes the controller circuit that may determine theoperating mode of the second sensor circuit including initiating dataacquisition if the sensed first signal satisfies a condition.

In Example 12, the subject matter of any one or more of Examples 1-11optionally includes the controller circuit that may determine theoperating mode of the second sensor circuit including adjusting dataacquisition rate if the sensed first signal satisfies a condition.

In Example 13, the subject matter of any one or more of Examples 1-12optionally includes the control circuit that may generate one or moresignal metrics from the sensed second signal under the determinedoperating mode, and generate the pain score using the generated one ormore signal metrics respectively weighted by weight factors.

In Example 14, the subject matter of any one or more of Examples 1-13optionally includes the control circuit that may generate the pain scorefurther using the sensed first signal.

In Example 15, the subject matter of any one or more of Examples 2-14optionally includes an implantable neuromodulator device that mayinclude one or more of the first sensor circuit, the second sensorcircuit, the controller circuit, or the electrostimulator.

Example 16 is a method for managing pain of a patient using animplantable neuromodulator device. The method comprises steps of:sensing a first signal indicative of a functional state of the patientvia a first sensor circuit; determining an operating mode of a secondsensor circuit using the sensed first signal; sensing a second signalvia the second sensor circuit under the determined operating mode, thesecond signal different from the first signal; generating a pain scoreusing at least the second signal sensed under the determined operatingmode; and outputting the pain score to a user or a process.

In Example 17, the subject matter of Example 16 optionally includesdelivering a pain therapy via the implantable neuromodulator device. Thepain therapy may include electrostimulation energy determined accordingto the pain score.

In Example 18, the subject matter of Example 16 optionally includesdetermining the operating mode of the second sensor circuit, which mayinclude initiating data acquisition if the sensed first signal satisfiesa condition.

In Example 19, the subject matter of Example 16 optionally includesdetermining the operating mode of the second sensor circuit, which mayinclude adjusting data acquisition rate if the sensed first signalsatisfies a condition.

In Example 20, the subject matter of Example 16 optionally includes thefirst signal that may include a physical activity signal. Thedetermining the operating mode of the second sensor circuit may includesteps of: comparing the sensed physical activity signal to an activitythreshold or to an activity template; initiating data acquisition of thesecond signal or acquiring the second signal at a first data acquisitionrate if the comparison satisfies a first condition; and withholding dataacquisition of the second signal or acquiring the second signal at asecond, lower data acquisition rate than the first data acquisition rateif the comparison satisfies a second condition indicating a higherphysical activity level.

In Example 21, the subject matter of Example 16 optionally includes thefirst signal that may include at least one of a posture signal, abalance signal, or a range-of-motion signal.

In Example 22, the subject matter of Example 16 optionally includes thesecond signal that may include at least one of a cardiac electricalactivity signal, an electromyography signal, a photoplethysmographysignal, a galvanic skin response signal, an electroencephalogram signal,or a hemodynamic signal.

In Example 23, the subject matter of Example 16 optionally includesgenerating one or more signal metrics from the sensed second signalunder the determined operating mode. The generating the pain scoreincludes using the generated one or more signal metrics respectivelyweighted by weight factors.

The pain score generated based on the functional signals, such as basedon the motor activity or sleep state signals as discussed in thisdocument, may improve medical diagnostics of automated characterizationof patient pain, as well as individualized therapies to alleviate painand to reduce side effects. The systems, devices, and methods discussedin this document may also enhance the performance and functionality of apain management system or device. A device or a system programmed withthe sensor-based pain assessment methods improves the automaticity inpain assessment. More efficient device memory or communication bandwidthusage may be achieved by storing or transmitting medical informationmore relevant to clinical decisions.

The systems and methods for pain assessment that use a first sensorsignal to trigger data acquisition and storage of a second sensorsignal, as discussed in this document, provide a power- andresource-conservative solution to ambulatory pain monitoring. Operatingmultiple sensors for pain assessment may put a high demand for batterypower, storage space, computing resources, and communication bandwidthon an ambulatory pain monitor. The triggered sensor activation and painassessment may not only reduce active operation time of thecorresponding device components, but also help ensure high-qualitysensor data (e.g., a higher data resolution) be collected in a specificpatient context (e.g., when the patient engage in a specific physicalactivity) and used for pain assessment. As such, the systems and methodsdiscussed herein may improve pain assessment accuracy and systemefficiency, but at lower operation cost. Additionally, through improvedpain therapy based on patient individual need and therapy efficacy,battery longevity of an implantable device may be enhanced, or painmedication volume may be saved.

This summary is intended to provide an overview of subject matter of thepresent patent application. It is not intended to provide an exclusiveor exhaustive explanation of the disclosure. The detailed description isincluded to provide further information about the present patentapplication. Other aspects of the disclosure will be apparent to personsskilled in the art upon reading and understanding the following detaileddescription and viewing the drawings that form a part thereof, each ofwhich are not to be taken in a limiting sense.

BRIEF DESCRIPTION OF THE DRAWINGS

Various embodiments are illustrated by way of example in the figures ofthe accompanying drawings. Such embodiments are demonstrative and notintended to be exhaustive or exclusive embodiments of the presentsubject matter.

FIG. 1 illustrates, by way of example and not limitation, aneuromodulation system and portions of an environment in which theneuromodulation system may operate.

FIG. 2 illustrates, by way of example and not limitation, a blockdiagram of a pain management system.

FIG. 3 illustrates, by way of example and not limitation, a blockdiagram of another pain management system.

FIG. 4 illustrates, by way of example and not limitation, a portion of apain management system for setting the operating mode of a second sensorcircuit using a signal sensed from a first sensor circuit.

FIG. 5 illustrates, by way of example and not limitation, a method formanaging pain of a patient.

FIG. 6 illustrates, by way of example and not limitation, a blockdiagram of an example machine upon which any one or more of thetechniques discussed herein may perform.

DETAILED DESCRIPTION

In the following detailed description, reference is made to theaccompanying drawings which form a part hereof, and in which is shown byway of illustration specific embodiments in which the invention may bepracticed. These embodiments are described in sufficient detail toenable those skilled in the art to practice the invention, and it is tobe understood that the embodiments may be combined, or that otherembodiments may be utilized and that structural, logical and electricalchanges may be made without departing from the spirit and scope of thepresent invention. References to “an”, “one”, or “various” embodimentsin this disclosure are not necessarily to the same embodiment, and suchreferences contemplate more than one embodiment. The following detaileddescription provides examples, and the scope of the present invention isdefined by the appended claims and their legal equivalents.

Clinically, chronic pain may affect a patient's functional state such asmotion control. Patient in pain may present with poor or unbalancedposture, abnormal gait pattern, restrained range-of-motion, or decreasedintensity or duration of physical activities. Pain may also cause bodyto compensate, such that muscles, ligaments and nerves may movedifferently to adapt to the pain. Over time, some muscles may becomechronically tight while other muscles weaken, and ligaments may stretchto accommodate uneven body motion. The compensatory changes in postureand the unbalanced motion pattern may gradually exacerbate the chronicpain and cause recurring injuries, resulting in a vicious pain cycle.

Chronic pain may also be associated with changes in patientphysiological conditions. Pain may impair neuro-cardiac integrity. Inthe presence of pain, elevated sympathetic activity and/or withdrawal ofparasympathetic activity may cause cardiovascular reactions, includingconstriction of peripheral blood vessels, increase in blood pressure,increase in heart rate, decrease in heart rate variability, and increasein cardiac force of contraction, among others. Alterations in autonomicfunction such as increased sympathetic tone may also affect cardiacelectrical activity, such as changes in electrocardiography (ECG)morphology or timing. In another example, chronic pain may be associatedwith muscle tension. When muscles remain being contracted for anextended period of time, blood flow to the soft tissues, includingmuscles, tendons, and nerves in the back may be reduced. Closemonitoring of patient muscle tension, such as detected fromelectromyography (EMG) or a mechanical contraction signal, may providean objective assessment of pain, and may be used to improve pain therapyefficacy.

Disclosed herein are systems, devices, and methods for or assessing painof a subject, and optionally programming pain therapy based on the painassessment. In various embodiments, the present system may include afirst sensor circuit to sense from the patient a first signal indicativeof a functional state of the patient, a second sensor circuit to sense asecond signal different from the first signal, and a controller circuit.The second signal may include a physiological signal or a functionalsignal. The controller circuit that may determine an operating mode ofthe second sensor circuit using the sensed first signal, trigger thesecond senor circuit to sense the second signal under the determinedoperating mode, and generate a pain score using at least the secondsignal sensed under the determined operating mode. The pain score can beoutput to a patient or used for closed-loop control of a pain therapy.

The present system may be implemented using a combination of hardwareand software designed to provide a closed-loop pain management regimento increase therapeutic efficacy, increase patient satisfaction forneurostimulation therapies, reduce side effects, and/or increase devicelongevity. The present system may be applied in any neurostimulation(neuromodulation) therapies, including but not limited to SCS, DBS, PNS,FES, and Vagus Nerve Stimulation (VNS) therapies. In various examples,instead of providing closed-loop pain therapies, the systems, devices,and methods described herein may be used to monitor the patient andassess pain that either occurs intrinsically, or is induced by nerveblock procedures or radiofrequency ablation therapies, among others. Thepatient monitoring may include generating recommendations to the patientor a clinician regarding pain treatment.

FIG. 1 illustrates, by way of example and not limitation, an example ofa neuromodulation system 100 for managing pain of a subject such as apatient with chronic pain, and portions of an environment in which theneuromodulation system 100 may operate. The neuromodulation system 100may include an implantable system 110 that may be associated with a body199 of the subject, and an external system 130 in communication with theimplantable system 110 via a communication link 120.

The implantable system 110 may include an ambulatory medical device(AMD), such as an implantable neuromodulator device (IND) 112, a leadsystem 114, and one or more electrodes 116. The IND 112 may beconfigured for subcutaneous implant in a patient's chest, abdomen, orother parts of the body 199. The IND 112 may be configured as amonitoring and diagnostic device. The IND 112 may include a hermeticallysealed can that houses sensing circuitry to sense physiological orfunctional signals from the patient via sensing electrodes or ambulatorysensors associated with the patient and in communication with the IND112. In some examples, the sensing electrodes or the ambulatory sensorsmay be included within the IND 112. The physiological or functionalsignals, when measured during a pain episode, may be correlative toseverity of the pain. The IND 112 may characterize and quantify thepain, such as to determine onset, intensity, severity, duration, orpatterns of the pain experienced by the subject. The IND 112 maygenerate an alert to indicate occurrence of a pain episode, painexacerbation, or efficacy of pain therapy, and present the alert to aclinician.

The IND 112 may alternatively be configured as a therapeutic device fortreating or alleviating the pain. In addition to the pain monitoringcircuitry, the IND 112 may further include a therapy unit that cangenerate and deliver energy or modulation agents to a target tissue. Theenergy may include electrical, magnetic, or other types of energy. Insome examples, the IND 112 may include a drug delivery system such as adrug infusion pump that can deliver pain medication to the patient, suchas morphine sulfate or ziconotide, among others.

The IND 112 may include electrostimulation circuitry that generateselectrostimulation pulses to stimulate a neural target via theelectrodes 116 operably connected to the IND 112. In an example, theelectrodes 116 may be positioned on or near a spinal cord, and theelectrostimulation circuitry may be configured to deliver SCS to treatpain. In another example, the electrodes 116 may be surgically placed atother neural targets such as a brain or a peripheral neutral tissue, andthe electrostimulation circuitry may be configured to deliver brain orperipheral stimulations. Examples of electrostimulation may include deepbrain stimulation (DBS), trigeminal nerve stimulation, occipital nervestimulation, vagus nerve stimulation (VNS), sacral nerve stimulation,sphenopalatine ganglion stimulation, sympathetic modulation, adrenalgland modulation, baroreceptor stimulation, or transcranial magneticstimulation, among other peripheral nerve or organ stimulation.

In various examples, the electrodes 116 may be distributed in one ormore leads of the lead system 114 electrically coupled to the IND 112.In an example, the lead system 114 may include a directional lead thatincludes at least some segmented electrodes circumferentially disposedabout the directional lead. Two or more segmented electrodes may bedistributed along a circumference of the lead. The actual number andshape of leads and electrodes may vary according to the intendedapplication. Detailed description of construction and method ofmanufacturing percutaneous stimulation leads are disclosed in U.S. Pat.No. 8,019,439, entitled “Lead Assembly and Method of Making Same,” andU.S. Pat. No. 7,650,184, entitled “Cylindrical Multi-Contact ElectrodeLead for Neural Stimulation and Method of Making Same,” the disclosuresof which are incorporated herein by reference. The electrodes 116 mayprovide an electrically conductive contact providing for an electricalinterface between the IND 112 and tissue of the patient. Theneurostimulation pulses are each delivered from the IND 112 through aset of electrodes selected from the electrodes 116. In various examples,the neurostimulation pulses may include one or more individually definedpulses, and the set of electrodes may be individually definable by theuser for each of the individually defined pulses.

Although the discussion herein with regard to the neuromodulation system100 focuses on an implantable device such as the IND 112, this is meantonly by way of example and not limitation. It is within thecontemplation of the present inventors and within the scope of thisdocument, that the systems, devices, and methods discussed herein mayalso be used for pain management via subcutaneous medical devices,wearable medical devices (e.g., wrist watch, patches, garment- orshoe-mounted device), or other external medical devices, or acombination of implantable, wearable, or other external devices. Thetherapy, such as electrostimulation or medical therapies, may be used totreat various neurological disorders other than pain, which by way ofexample and not limitation may include epilepsy, obsessive compulsivedisorder, tremor, Parkinson's disease, or dystonia, among other movementand affective disorders.

The external system 130 may be communicated with the IND 112 via acommunication link 120. The external system 130 may include a dedicatedhardware/software system such as a programmer, a remote server-basedpatient management system, or alternatively a system definedpredominantly by software running on a standard personal computer. Theexternal system 130 may be configured to control the operation of theIND 112, such as to program the IND 112 for delivering neuromodulationtherapy. The external system 130 may additionally receive via thecommunication link 120 information acquired by IND 112, such as one ormore physiological or functional signals. In an example, the externalsystem 130 may determine a pain score based on the physiological orfunctional signals received from the IND 112, and program the IND 112 todeliver pain therapy in a closed-loop fashion. Examples of the externalsystem and neurostimulation based on pain score are discussed below,such as with reference to FIGS. 2-3.

The communication link 120 may include one or more communicationchannels and intermediate devices between the external system and theIND, such as a wired link, a telecommunication link such as an internetconnection, or a wireless link such as one or more of an inductivetelemetry link, a radio-frequency telemetry link. The communication link120 may provide for data transmission between the IND 112 and theexternal system 130. The transmitted data may include, for example,real-time physiological or functional signals acquired by and stored inthe IND 112, therapy history data, data indicating device operationalstatus of the IND 112, one or more programming instructions to the IND112 which may include configurations for sensing physiologic signal orstimulation commands and stimulation parameters, or deviceself-diagnostic test, among others. In some examples, the IND 112 may becoupled to the external system 130 further via an intermediate controldevice, such as a handheld external remote control device to remotelyinstruct the IND 112 to generate electrical stimulation pulses inaccordance with selected stimulation parameters produced by the externalsystem 130.

Portions of the IND 112 or the external system 130 may be implementedusing hardware, software, firmware, or combinations thereof. Portions ofthe IND 112 or the external system 130 may be implemented using anapplication-specific circuit that may be constructed or configured toperform one or more particular functions, or may be implemented using ageneral-purpose circuit that may be programmed or otherwise configuredto perform one or more particular functions. Such a general-purposecircuit may include a microprocessor or a portion thereof, amicrocontroller or a portion thereof, or a programmable logic circuit,or a portion thereof. For example, a “comparator” may include, amongother things, an electronic circuit comparator that may be constructedto perform the specific function of a comparison between two signals orthe comparator may be implemented as a portion of a general-purposecircuit that may be driven by a code instructing a portion of thegeneral-purpose circuit to perform a comparison between the two signals.

FIG. 2 illustrates, by way of example and not limitation, an example ofa pain management system 200, which may be an embodiment of theneuromodulation system 100. The pain management system 200 may assesspain of a subject using functional or physiological signals. Asillustrated in FIG. 2, the pain management system 200 may include afirst sensor circuit 210, a second sensor circuit 220, a pain analyzercircuit 230, a controller circuit 240, and a user interface 250. In someexamples, the pain analyzer circuit 230 may be part of the controllercircuit 240. The pain management system 200 may additionally include atherapy circuit 260 to deliver pain therapy such as according to thepain assessment.

The first sensor circuit 210 may be configured to sense a first signalindicative of functional state of the subject. The first sensor circuit210 may be coupled to a motion sensor to sense at least one functionalsignal. The motion sensor may be an ambulatory sensor, such as animplantable or wearable sensor associated with the patient. Additionallyor alternatively, the motion sensor may be a stationary sensor, such asmounted in a room or attached to furniture, to detect one or morefunctional signals from the patient when the patient enters, or remainswithin, an environment of patient daily life.

The first sensor circuit 210 may include sense amplifier circuit thatmay pre-process the sensed signals, including, for example,amplification, digitization, filtering, or other signal conditioningoperations. In an example, the functional signal may include a motoractivity signal. Examples of the motor activity signal may include, butare not limited to, patient posture, gait, balance, or physical activitysignals, among others. In another example, the functional signal mayinclude a sleep state signal that contains information about sleepdisturbance. Chronic pain patients may experience frequent disruptedsleep or change of sleep patterns. The motion sensor may detectfrequency or duration of sleep position switch, sleep incline, or otherindicators of sleep quality. Examples of the sensors for detectingvarious functional signals are discussed below, such as with referenceto FIG. 4.

The second sensor circuit 220 may sense from the subject a second signaldifferent from the first signal sensed from the first sensor circuit210. The second sensor circuit 220 may be coupled to an ambulatorysensor or a stationary sensor to sense one or more physiological signalsor one or more functional signals different from the first signal. Thephysiological signals may reveal characteristic signal properties inresponse to an onset, intensity, severity, duration, or patterns ofpain. Information of physiological signal changes may be used to assesspatient pain.

Pain may impair neuro-cardiac integrity. In the presence of pain,elevated sympathetic activity and/or withdrawal of parasympatheticactivity may cause cardiovascular reactions, such as increased heartrate, enhanced cardiac force, and changes in electrical activity.Examples of the cardiac signals can include a heart rate signal, a pulserate signal, a heart rate variability signal, electrocardiograph (ECG)or intracardiac electrogram, cardiovascular pressure signal, or heartsounds signal, among others.

In addition to or in lieu of the cardiac signals, the second sensorcircuit 220 may sense one or more of a galvanic skin response (GSR)signal, an electrodermal activity (EDA) signal, a skin temperaturesignal, an electromyogram (EMG) signal, an electroencephalogram (EEG)signal, a magnetoencephelogram (MEG) signal, a hemodynamic signal suchas a blood flow signal, a blood pressure signal, a blood perfusionsignal, a photoplethysmography (PPG) signal, a heart sound signal, or asaliva production signal indicating the change of amount of salivaproduction, among others. The physiological signals may additionallyinclude pulmonary, neural, or biochemical signals. Examples of pulmonarysignals may include a respiratory signal, a thoracic impedance signal,or a respiratory sounds signal. Examples of biochemical signals mayinclude blood chemistry measurements or expression levels of one or morebiomarkers, which may include, by way of example and not limitation,B-type natriuretic peptide (BNP) or N-terminal pro b-type natriureticpeptide (NT-proBNP), serum cytokine profiles, P2X4 receptor expressionlevels, gamma-aminobutyric acid (GABA) levels, TNFα and otherinflammatory markers, cortisol, adenosine, Glial cell-derivedneurotrophic factor (GDNF), Nav 1.3, Nav 1.7, or Tetrahydrobiopterin(BH4) levels, among other biomarkers.

The pain analyzer circuit 230 may generate a pain score using at leastthe second signal received from the second sensor circuit 220. In someexamples, the pain analyzer circuit 230 generate the pain score furtherusing the functional signal sensed from the first sensor circuit 210.The pain analyzer circuit 230 may be implemented as a part of amicroprocessor circuit, which may be a dedicated processor such as adigital signal processor, application specific integrated circuit(ASIC), microprocessor, or other type of processor for processinginformation including physical activity information. Alternatively, themicroprocessor circuit may be a general-purpose processor that mayreceive and execute a set of instructions of performing the functions,methods, or techniques described herein.

As illustrated in FIG. 2, the pain analyzer circuit 230 may be coupledto a controller circuit 240 that controls the sensor-based painassessment. In some examples, the pain analyzer circuit 230 may be partof the controller circuit 240. The controller circuit 240 may receivethe first signal sensed from the first sensor circuit 210. Thecontroller circuit 240 includes an operating mode control 242 that maydetermine an operating mode of the second sensor circuit 220 using thereceived first signal. The operating mode controls the data acquisitionand data processing at the second sensor circuit 220, and may include anactivation or deactivation of sensor data acquisition, or a dataacquisition rate such as a sampling rate or a digitization resolution.Using the first sensor signal to trigger activation and to set anoperating mode of the second sensor may help improve system or devicefunction of chronic and ambulatory. Activation and operation of multiplesensors for physiological data acquisition can be power- andmemory-demanding, and pain assessment may require substantial amount ofcomputing resource. The activation of and operating mode triggered bythe first sensor, such as controlled by the controller circuit 240, mayreduce the activation time of the second sensor, conserve the devicepower and computing resources, and thus reduces the operational cost.

The operating mode control 242 may compare the first signal to acondition, such as a threshold or a value range. Based on thecomparison, the operating mode control 242 may determine the operatingmode of the second sensor circuit 220, such as whether to activate ordeactivate data acquisition, time of data acquisition, or a samplingrate for acquiring the second signal. The comparison may indicate anonset of a pain episode or worsening of pain. Activating the dataacquisition of the second signal and pain assessment using the secondsignal may more reliably confirm the pain episode or the worsening ofpain. In some examples, the comparison may additionally or alternativelybe used to prescreen the second sensor to determine a proper time toacquire data such as to avoid interferences or noise. This may allow forhigh-quality data being used in pain assessment. Examples of setting theoperating mode of the second sensor circuit using the first sensedsignal are discussed as follows, such as with reference to FIG. 4.

The pain analyzer circuit 230 and the controller circuit 240 may eachinclude respective circuit sets comprising one or more other circuits orsub-circuits. In an example as illustrated in FIG. 2, the pain analyzercircuit 230 may comprise a signal metric generator 231 and a pain scoregenerator 232. These circuits or sub-circuits may, alone or incombination, perform the functions, methods or techniques describedherein. In an example, hardware of the circuit set may be immutablydesigned to carry out a specific operation (e.g., hardwired). In anexample, the hardware of the circuit set may include variably connectedphysical components (e.g., execution units, transistors, simplecircuits, etc.) including a computer readable medium physically modified(e.g., magnetically, electrically, moveable placement of invariantmassed particles, etc.) to encode instructions of the specificoperation. In connecting the physical components, the underlyingelectrical properties of a hardware constituent are changed, forexample, from an insulator to a conductor or vice versa. Theinstructions enable embedded hardware (e.g., the execution units or aloading mechanism) to create members of the circuit set in hardware viathe variable connections to carry out portions of the specific operationwhen in operation. Accordingly, the computer readable medium iscommunicatively coupled to the other components of the circuit setmember when the device is operating. In an example, any of the physicalcomponents may be used in more than one member of more than one circuitset. For example, under operation, execution units may be used in afirst circuit of a first circuit set at one point in time and reused bya second circuit in the first circuit set, or by a third circuit in asecond circuit set at a different time.

The signal metric generator 231 may generate one or more signal metricsfrom the sensed second signal under the determined operating mode. Thesignal metrics may include statistical parameters extracted from thesensed signal, such as signal mean, median, or other central tendencymeasures or a histogram of the signal intensity, among others. Thesignal metrics may additionally or alternatively include morphologicalparameters such as maximum or minimum within a specific time period suchas a cardiac cycle, positive or negative slope or higher orderstatistics, or signal power spectral density at a specific frequencyrange, among other morphological parameters. The signal metrics mayadditionally include timing information such as a time interval betweena first characteristic point in one signal and a second characteristicpoint in another signal. In various examples, the signal metricgenerator 231 may extract from the second signal, sensed under thedetermined operating mode, one or more ECG metrics such as heart rate,heart rate variability, timing relationship between characteristic ECGcomponents (e.g., P wave to R wave intervals), PPG metrics, bloodpressure metrics, pulse wave transit metrics, EMG metrics, muscletightness metrics, muscle shortening metrics, EEG metrics, GSR metrics,among others. In some examples, the signal metric generator circuit 231may additionally generate from the sensed first signal a plurality offunctional signal metrics indicative of patient functional state such asmotor control or kinetics. By way of example and not limitation, themotor activity metrics may include metrics of posture, gait, physicalactivity, balance, or range-of-motion.

The pain score generator 232 may generate a pain score using the signalmetrics generated from the second signal sensed under the determinedoperating mode, or optionally along with the signal metrics generatedfrom the first functional signal metrics. The pain score can berepresented as a numerical or categorical value that quantifies thepatient's overall pain symptom. In an example, a composite signal metricmay be generated using a combination of a plurality of the signalmetrics respectively weighted by weight factors. The combination can belinear or nonlinear. The pain score generator 232 may compare thecomposite signal metric to one or more threshold values or range values,and assign a corresponding pain score (such as numerical values from 0to 10) based on the comparison.

In another example, the pain score generator 232 may compare the signalmetrics to their respective threshold values or range values, assigncorresponding signal metric-specific pain scores based on thecomparison, and compute a composite pain score using a linear ornonlinear fusion of the signal metric-specific pain scores weighted bytheir respective weight factors. In an example, the threshold can beinversely proportional to signal metric's sensitivity to pain. A signalmetric that is more sensitive to pain may have a corresponding lowerthreshold and a larger metric-specific pain score, thus plays a moredominant role in the composite pain score than another signal metricthat is less sensitive to pain. Examples of the fusion algorithm mayinclude weighted averages, voting, decision trees, or neural networks,among others. The pain score generated by the pain score generator 232may be output to a system user or a process.

The user interface 250 may include an input circuit and an outputcircuit. In an example, at least a portion of the user interface 250 maybe implemented in the external system 130. The input circuit may enablea system user to program the parameters used for sensing thephysiological signals, generating signal metrics, or generating the painscore. The input circuit may be coupled to one or more input devicessuch as a keyboard, on-screen keyboard, mouse, trackball, touchpad,touch-screen, or other pointing or navigating devices. In some example,the input device may be incorporated in a mobile device such as a smartphone or other portable electronic device with a mobile application(“App”). The mobile App may enable a patient to provide pain descriptionor quantified pain scales during the pain episodes. In an example, theinput circuit may enable a user to confirm, reject, or edit theprogramming of the therapy circuit 260, such as parameters forelectrostimulation, as to be discussed in the following.

The output circuit may be coupled to a display to present to a systemuser such as a clinician the pain score, physiological and functionalsignals sensed from the sensor circuits 210 and 220, trends of thesignal metric, or any intermediary results for pain score calculationsuch as the signal metric-specific pain scores. In some examples, aclinician may assess efficacy of paint treatment using the sensedphysiological and functional signals. For example, a patient may becometoo active too quickly after improvement in pain symptoms or having painrelief. The output of the functional signal such as physical activitytrend may aid a clinician in advising the patient to decrease activityor to track an acceptable activity routine through the treatmentprocess. The information may be presented in a table, a chart, adiagram, or any other types of textual, tabular, or graphicalpresentation formats, for displaying to a system user. The presentationof the output information may include audio or other human-perceptiblemedia format. In an example, the output circuit may generate alerts,alarms, emergency calls, or other means of warnings to signal the systemuser about the detected pain score.

The therapy circuit 260 may be configured to deliver a therapy to thepatient based on the pain score generated by the pain score generator232. The therapy circuit 260 may include an electrostimulator configuredto generate electrostimulation energy to treat pain, or to alleviateside effects introduced by the electrostimulation of the target tissue.In an example, the electrostimulator may deliver spinal cord stimulation(SCS) via electrodes electrically coupled to the electrostimulator. Theelectrodes may be surgically placed at a region at or near a spinal cordtissue, which may include, by way of example and not limitation, dorsalcolumn, dorsal horn, spinal nerve roots such as the dorsal nerve root,and dorsal root ganglia. The SCS may be in a form of stimulation pulsesthat are characterized by pulse amplitude, pulse width, stimulationfrequency, duration, on-off cycle, pulse shape or waveform, temporalpattern of the stimulation, among other stimulation parameters. Examplesof the stimulation pattern may include burst stimulation withsubstantially identical inter-pulse intervals, or ramp stimulation withincremental inter-pulse intervals or with decremental inter-pulseintervals. In some examples, the frequency or the pulse width may changefrom pulse to pulse. The electrostimulator may additionally oralternatively deliver electrostimulation to other target tissues such asperipheral nerves tissues. In an example, the electrostimulator maydeliver transcutaneous electrical nerve stimulation (TENS) viadetachable electrodes that are affixed to the skin. Other examples ofelectrostimulation may include deep brain stimulation (DBS), trigeminalnerve stimulation, occipital nerve stimulation, vagus nerve stimulation(VNS), sacral nerve stimulation, sphenopalatine ganglion stimulation,sympathetic modulation, adrenal gland modulation, baroreceptorstimulation, or transcranial magnetic stimulation, among otherperipheral nerve or organ stimulation.

The therapy circuit 260 may additionally or alternatively include a drugdelivery system, such as an intrathecal drug delivery pump that may besurgically placed under the skin, which may be programmed to injectmedication through a catheter to the area around the spinal cord. Otherexamples of drug delivery system may include a computerizedpatient-controlled analgesia pump that may deliver the prescribed painmedication to the patient such as via an intravenous line.

The controller circuit 240 may control the therapy circuit 260 togenerate and deliver pain therapy, such as neurostimulation energy,according to the pain score received from the pain score generator 232.The controller circuit 240 may control the generation ofelectrostimulation pulses according to specific stimulation parameters.Additionally or alternatively, the controller circuit 240 may controlthe therapy circuit 260 to deliver electrostimulation pulses viaspecific electrodes. In an example of pain management via SCS, aplurality of segmented electrodes, such as the electrodes 116, may bedistributed in one or more leads. The controller circuit 240 mayconfigure the therapy circuit 260 to deliver electrostimulation pulsesvia a set of electrodes selected from the plurality of electrodes. Theelectrodes may be manually selected by a system user or automaticallyselected based on the pain score.

FIG. 3 illustrates, by way of example and not limitation, anotherexample of a pain management system 300, which may be an embodiment ofthe neuromodulation system 100 or the pain management system 200. Thepain management system 300 may include an implantable neuromodulator 310and an external system 320, which may be, respectively, embodiments ofthe IND 112 and the external system 130 as illustrated in FIG. 1. Theexternal system 320 may be communicatively coupled to the implantableneuromodulator 310 via the communication link 120.

The implantable neuromodulator 310 may include several components of thepain management system 200 as illustrated in FIG. 2, including the firstsensor circuit 210, the second sensor circuit 220, the pain analyzercircuit 230, the controller circuit 240, and the therapy circuit 260. Aspreviously discussed, in some examples, the pain analyzer circuit 230may be part of the controller circuit 240. The implantableneuromodulator 310 may include a memory circuit 370 configured to storesensor signals or signal metrics such as generated by the first sensorcircuit 210, the second sensor circuit 220, the signal metric generator231, and the pain scores such as generated by the pain score generator232. Data storage at the memory circuit 370 may be continuous, periodic,or triggered by a user command or a specific event. The memory circuit370 may store weight factors used for generating the composite painscore, such as at the pain score generator 232. The weight factors maybe provided by a system user, or alternatively be automaticallydetermined or adjusted such as based on the corresponding signalmetrics' reliability in representing an intensity of the pain.

The controller circuit 240 may control the generation ofelectrostimulation pulses according to specific stimulation parameters.The stimulation parameters may be provided by a system user.Alternatively, the stimulation parameters may be automaticallydetermined based on the intensity, severity, duration, or pattern ofpain, which may be subjectively described by the patient, orautomatically quantified based on the signals sensed by the sensorcircuits 210 and 220. For example, when a patient-described orsensor-indicated pain quantification exceeds a respective thresholdvalue or falls within a specific range indicating elevated pain, theelectrostimulation energy may be increased to provide stronger painrelief. Increased electrostimulation energy may be achieved byprogramming a higher pulse intensity, a higher frequency, or a longerstimulation duration or “on” cycle, among others. Conversely, when apatient-described or sensor-indicated pain quantification falls below arespective threshold value or falls within a specific range indicatingno pain or mild pain, the electrostimulation energy may be decreased.

The implantable neuromodulator 310 may receive the information aboutelectrostimulation parameters and the electrode configuration from theexternal system 320 via the communication link 120. Additionalparameters associated with operation of the therapy circuit 260, such asbattery status, lead impedance and integrity, or device diagnostic ofthe implantable neuromodulator 310, may be transmitted to the externalsystem 320. The controller circuit 240 may control the generation anddelivery of electrostimulation using the information aboutelectrostimulation parameters and the electrode configuration from theexternal system 320. Examples of the electrostimulation parameters andelectrode configuration may include: temporal modulation parameters suchas pulse amplitude, pulse width, pulse rate, or burst intensity;morphological modulation parameters respectively defining one or moreportions of stimulation waveform morphology such as amplitude ofdifferent phases or pulses included in a stimulation burst; or spatialmodulation parameters such as selection of active electrodes, electrodecombinations which define the electrodes that are activated as anodes(positive), cathodes (negative), and turned off (zero), and stimulationenergy fractionalization which defines amount of current, voltage, orenergy assigned to each active electrode and thereby determines spatialdistribution of the modulation field.

In an example, the controller circuit 240 may control the generation anddelivery of electrostimulation in a closed-loop fashion by adaptivelyadjusting one or more stimulation parameters or stimulation electrodeconfiguration based on the pain score. For example, if the score exceedsthe pain threshold (or falls within a specific range indicating anelevated pain), then the first electrostimulation may be delivered.Conversely, if the composite pain score falls below a respectivethreshold value (or falls within a specific range indicating no pain ormild pain), then a second pain therapy, such as secondelectrostimulation may be delivered. The first electrostimulation maydiffer from the second electrostimulation with respect to at least oneof the stimulation energy, pulse amplitude, pulse width, stimulationfrequency, duration, on-off cycle, pulse shape or waveform,electrostimulation pattern such as electrode configuration or energyfractionalization among active electrodes, among other stimulationparameters. In an example, the first electrostimulation may have higherenergy than the second electrostimulation, such as to provide strongereffect of pain relief. Examples of increased electrostimulation energymay include a higher pulse intensity, a higher frequency, or a longerstimulation duration or “on” cycle, among others.

The parameter adjustment or stimulation electrode configuration may beexecuted continuously, periodically at specific time, duration, orfrequency, or in a commanded mode upon receiving from a system user acommand or confirmation of parameter adjustment. In some examples, theclosed-loop control of the electrostimulation may be further based onthe type of the pain, such as chronic or acute pain. In an example, thepain analyzer circuit 230 may trend the signal metric over time tocompute an indication of abruptness of change of the signal metrics,such as a rate of change over a time period. The pain episode may becharacterized as acute pain if the signal metric changes abruptly (e.g.,the rate of change of the signal metric exceeding a threshold), or aschronic pain if the signal metric changes gradually (e.g., the rate ofchange of the signal metric falling below a threshold). The controllercircuit 240 may control the therapy circuit 260 to deliver, withhold, orotherwise modify the pain therapy in accordance with the pain type. Forexample, incidents such as toe stubbing or bodily injuries may causeabrupt changes in certain signal metrics, but no adjustment of theclosed-loop pain therapy is deemed necessary. On the contrary, if thepain analyzer circuit 230 detects chronic pain characterized by gradualsignal metric change, then the closed-loop pain therapy may be deliveredaccordingly.

The external system 320 may include the user interface 250, a weightgenerator 322, and a programmer circuit 324. The weight generator 322may generate weight factors used by the pain score generator 232 togenerate the pain score. The weight factors may indicate the signalmetrics' reliability in representing an intensity of the pain. A sensormetric that is more reliable, or more sensitive or specific to the pain,would be assigned a larger weight than another sensor metric that isless reliable, or less sensitive or specific to the pain. In an example,the weight factors may be proportional to correlations between aplurality of quantified pain scales (such as reported by a patient) andmeasurements of the measurements of the signal metrics corresponding tothe plurality of quantified pain scales. A signal metric that correlateswith the pain scales is deemed a more reliable signal metric for painquantification, and is assigned a larger weight factor than anothersignal metric less correlated with the quantified pain scales. Inanother example, the weight generator 322 may determine weight factorsusing the signal sensitivity to pain. The signal metrics may be trendedover time, such as over approximately six months. The signal sensitivityto pain may be represented by a rate of change of the signal metricsover time during a pain episode. The signal sensitivity to pain may beevaluated under a controlled condition such as when the patient postureor activity is at a specific level or during specific time of the day.The weight generator 322 may determine weight factors to be proportionalto signal metric's sensitivity to pain.

The programmer circuit 324 may produce parameter values for operatingthe implantable neuromodulator 310, including parameters for sensing thesignals and generating signal metrics, and parameters or electrodeconfigurations for electrostimulation. In an example, the programmercircuit 324 may generate the stimulation parameters or electrodeconfigurations for SCS based on the pain score produced by the painscore generator 232. Through the communication link 120, the programmercircuit 324 may continuously or periodically provide adjustedstimulation parameters or electrode configuration to the implantableneuromodulator 210. By way of non-limiting example and as illustrated inFIG. 3, the programmer circuit 324 may be coupled to the user interface250 to allow a user to confirm, reject, or edit the stimulationparameters, sensing parameters, or other parameters controlling theoperation of the implantable neuromodulator 210. The programmer circuit324 may also adjust the stimulation parameter or electrode configurationin a commanded mode upon receiving from a system user a command orconfirmation of parameter adjustment.

The programmer circuit 324, which may be coupled to the weight generator322, may initiate a transmission of the weight factors generated by theweight generator 322 to the implantable neuromodulator 310, and storethe weight factors in the memory circuit 370. In an example, the weightfactors received from the external system 320 may be compared topreviously stored weight factors in the memory circuit 370. Thecontroller circuit 240 may update the weight factors stored in thememory circuit 370 if the received weight factors are different from thestored weights. The pain analyzer circuit 230 may use the updated weightfactors to generate a pain score. In an example, the update of thestored weight factors may be performed continuously, periodically, or ina commanded mode upon receiving a command from a user.

In some examples, the pain score may be used by a therapy unit (such asan electrostimulator) separated from the pain management system 300. Invarious examples, the pain management system 300 may be configured as amonitoring system for pain characterization and quantification withoutdelivering closed-loop electrostimulation or other modalities of paintherapy. The pain characterization and quantification may be provided toa system user such as the patient or a clinician, or to a processincluding, for example, an instance of a computer program executable ina microprocessor. In an example, the process includescomputer-implemented generation of recommendations or an alert to thesystem user regarding pain medication (e.g., medication dosage and timefor taking a dose), electrostimulation therapy, or other pain managementregimens. The therapy recommendations or alert may be based on the painscore, and may be presented to the patient or the clinician in varioussettings including in-office assessments (e.g. spinal cord stimulationprogramming optimization), in-hospital monitoring (e.g. opioid dosingduring surgery), or ambulatory monitoring (e.g. pharmaceutical dosingrecommendations).

In an example, in response to the pain score exceeding a threshold thatindicates an elevated pain symptom, an alert may be generated andpresented at the user interface 250 to remind the patient to take painmedication. In another example, therapy recommendations or alerts may bebased on information about wearing-off effect of pain medication, whichmay be stored in the memory circuit 370 or received from the userinterface 250. When the drug effect has worn off, an alert may begenerated to remind the patient to take another dose or to request aclinician review of the pain prescription. In yet another example,before a pain therapy such as neurostimulation therapy is adjusted (suchas based on the pain score) and delivered to the patient, an alert maybe generated to forewarn the patient or the clinician of any impendingadverse events. This may be useful as some pain medication may havefatal or debilitating side effects. In some examples, the painmanagement system 300 may identify effect of pain medication addictionsuch as based on functional and physiological signals. An alert may begenerated to warn the patient about effects of medication addiction andthus allow medical intervention.

FIG. 4 illustrates, by way of example and not limitation, an example ofa portion of a pain management system for setting the operating mode ofthe second sensor circuit 220 using a signal sensed from a first sensorcircuit 420. The system portion may include one or more motion sensors410, a first sensor circuit 420 which an embodiment of the first sensorcircuit 210, the controller circuit 240, and the signal second sensorcircuit 220. The signals acquired at the second sensor circuit 220 underthe operating mode may be used by the pain management system 200 or 300to characterize and quantify patient.

By way of example and not limitation, the motion sensors 410 may includeone or more of sensors 411-415 that may sense patient functional state.The physical activity sensor 411 may include an accelerometer configuredto sense a physical activity signal. The accelerometer may besingle-axis or multi-axis accelerometer. The posture sensor 412 mayinclude a tilt switch or a single- or multi-axis accelerometerassociated with the patient. For example, the posture sensor may bedisposed external to the body or implanted inside the body. Posture maybe represented by, for example, a tilt angle. In some examples, postureor physical activity information may be derived from thoracic impedanceinformation. The motion range sensor 413 may include an accelerometerpositioned on patient extremities or patient body trunk to detect arange-of-motion. The gait sensor 414 may detect patient gait or a stateof balance. Examples of the gait sensors may include accelerometer,gyroscope (which may be a one-, two-, or three-axis gyroscope),magnetometer (e.g., a compass), inclinometers, goniometers,electromagnetic tracking system (ETS), a global positioning system (GPS)sensor, sensing fabric, force sensor, strain gauges, and sensors forelectromyography (EMG). The sensors may be configured for wearing at, orattaching to, patient foot, ankle, leg, waist, or other parts on thetorso or the extremities. In an example, the gait sensor 414 may includean insole force sensor for placement inside a shoe or a boot. The insoleforce sensor may take the form of a strain gauge, a piezoelectricsensor, or a capacitive sensor, among others. The insole force sensormay be wirelessly coupled to the IND 310 or the pain analyzer circuit230. The first sensor circuit 210 may analyze force distribution on apatient's foot, and generate an indicator of gait. The sleep statesensor 415 may include an accelerometer, a piezoelectric sensor,biopotential electrodes and sensors, or other sensors to detect thesleep state of the patient.

The motion sensors 410 may be associated with a patient in variousmanners. In an example, one or more of the motion sensors 410 may beimplantable sensors configured for subcutaneous implantation at variousbody locations. One or more of the motion sensors 410 may be wearablesensors configured to be worn on the head, wrist, hand, foot, ankle,waist, or other parts of the body, or apparel-mounted sensor that may bemounted on a garment, a footwear, a headwear, or one or more accessoriescarried by the patient, such as a pendant, a necklace, or a bracelet. Inanother example, one or more of the motion sensors 410 may be stationarysensors configured for placement in patient environment, such as at abedside, in a room at patient home, or in a testing room at a clinic ormedical facility. In an example, the motion sensors may be mounted on achair, a bed (e.g., under or attached to a mattress), or a fixture in apatient's environment. Unlike the implantable, wearable, orapparel-mounted sensors which are ambulatory in nature, the stationarysensors are configured to detect one or more functional signals when thepatient enters, or remains within, an environment within the scope ofsurveillance of the stationary sensor. In an example, the stationarysensors may include a camera or a video recorder configured to capturean image, an image sequence, or a video of the patient at a specificphysical state, such as sitting, standing, walking, or doing physicalactivities. In an example, the camera may be an infrared camera. In anexample, the camera is a digital camera that may generate digital datarepresentation of an image or a video sequence.

In some examples, one or more of the motion sensors 410 may beincorporated in a mobile device, such as a smart phone, a wearabledevice, a fitness band, a portable health monitor, a tablet, a laptopcomputer, among other portable computerized device. For example, one ormore of an accelerometer, a gyroscope, a magnometer, a GPS sensor, or acamera that sense motor activity signals may be embedded in a mobiledevice. The mobile device may be communicatively coupled to the IND 310or the pain analyzer circuit 230 via a communication link such as auniversal serial bus connection, a Bluetooth protocol, Ethernet, IEEE802.11 wireless, an inductive telemetry link, or a radio-frequencytelemetry link, among others.

The first sensor circuit 420, an embodiment of the first sensor circuit210, may be coupled to the motion sensors 410 via wired or wirelessconnections. The first sensor circuit 420 may include a sense amplifiercircuit that may pre-process the sensed functional signal, and a featureextractor circuit 421 that may extract one or more motor activityfeatures from the processed functional signals. In an example, featuresextracted from the physical activity signal may include one or more ofactivity intensity, activity duration, or a transition time betweendifferent types of activities. A decrease in activity intensity orduration from an activity baseline such as established using patienthistorical activity signals, or less frequent transition or an increasein transition time from one activity to another may indicate painsuffered by the patient. In another example, features extracted from theposture signal may include body position during sitting, standing, orwalking. A decrease in activity intensity or duration from an activitybaseline such as established using patient historical activity signals,or less frequent transition or an increase in transition time from oneactivity to another may indicate pain suffered by the patient. In anexample, features extracted from the motion range signal may includelumbar forward flexion, shoulder flexion, elbow flexion, rotation of armand elbow joint, trunk-pelvis rotation, or other motor control andkinematic features. The motion range feature may include indication ofsmoothness of motion, such as a rate or a pattern of change in motionwith respect to time, or with respect to angular velocity, etc. Inanother example, features extracted from the gait signal or balancesignal may include velocity, time to peak velocity, step length, stridelength, stride width, swing time, single limb support time, double limbstance, gait autonomy, cadence, among other measurements. In yet anotherexample, features extracted from the sleep state signal may includesleep incline, sleep sidedness, frequency of sleep position switch, orother sleep quality or sleep disturbance metrics. For example, anincrease in sleep incline, or enhanced frequency of body positionswitches during sleep, or reduced sleep duration are indicators ofincrease pain. The sleep state features, when satisfying a conditionthat indicates occurrence or aggravation of a pain episode, may triggerone or more other sensors to sense physiological or functional signals.In an example, if the frequency of sleep position switch exceeds athreshold, or if the sleep duration at a sleep position falls below athreshold (e.g., less than 5-15 seconds), sleep disturbance isindicated, which may trigger other sensors for sensing heart rate,respiration rate, jaw clench, or other physiological or functionalresponses. The sensed response may be used to distinguish between normalsleep patterns (e.g., sleep position change) and abnormal sleep patternscaused by or otherwise associated with acute pain.

Measurements of the extracted feature may be trended over time. Thecomparator 422 may compare the extracted feature trend to one or morethresholds or one or more value ranges to determine patient functionalstate. The operating mode control 242 in the controller circuit 240 maydetermine an operating mode for the second sensor circuit 220 accordingto the comparison. In an example, the comparator 422 may compare one ormore features extracted from the physical activity signal to determinepatient physical activity level. Physical activity level may indicatepresence or severity of pain. Patient in pain are generally less active,such that periods of activity are generally shorter and activityintensity is generally lower. If the comparison at the comparator 422indicates a low physical activity level (in activity intensity orduration), then a pain episode or precursor of pain has likely occurred.The operating mode control 242 may activate the second sensor circuit220 to initiate sensing signals such as cardiac, pulmonary, muscular, orneurological signals. However, if the comparison at the comparator 422indicates a high physical activity level, then the patient is not likelyexperiencing pain. The operating mode control 242 may at leasttemporarily deactivate the second sensor circuit 220 from sensing dataif the second sensor circuit 220 is in an active data-acquisition mode,or control the second sensor circuit 220 to withhold data acquisition.

In some examples, the extracted feature of physical activity may bemeasured during a specified time period of daytime or nighttime, or in aspecific context such as when the patient is asleep. For example, if ahigh physical activity level is detected by the comparator 422 using thephysical activity features extracted during a period of nighttime, orthe high physical activity level is accompanied a detection of sleepsuch as detected by the sleep state sensor 415, the detected highphysical activity level may indicate an onset of pain, worsening ofpain, or undesirable pain treatment. The operating mode control 242 mayactivate the second sensor circuit 220 or acquire the data at a highdata acquisition rate.

The first sensor circuit 422 may include a pattern detector 423 todetect a physical activity pattern using measurements of the extractedfeature over time, such as collected within a specific time periodduring daytime or nighttime. The activity pattern may indicate thetemporal variation of the physical activity during the specific timeperiod. The comparator 422 may compare the detected physical activitypattern to a physical activity template representing a physical activitypattern under a known, controlled condition, such as a baselinepain-free condition. The physical activity template may be generatedusing the historical activity data from the same patient, or usingactivity data from a patient population. The comparator 422 may computea dissimilarity measure, such as a distance measure, between thedetected physical activity pattern and the physical activity templaterepresenting activity pattern during a pain-free condition. For example,pain patients tend to decrease activity during the course of a day,while healthy subjects generally have more stable daily activity levels.The pattern detector 423 may compute a decay rate of activity levelduring a time period (such as during a 12-hour period from morning toevening), and the comparator 422 may determine a dissimilarity of thedecay rate of the detected physical activity and the decay rate of thephysical activity template. If the dissimilarity exceeds a threshold,then the detected physical activity pattern indicates a high likelihoodof pain. The operating mode control 242 may activate the second sensorcircuit 220, or acquire the data at a high data rate mode. In someexamples, the physical activity template may represent physical activitypattern under other known conditions, such as when the patient is inpain, walking, sitting still, or any other form of activity. In anotherexample, the physical activity template may represent patient regularactivity (e.g. daily jog) during a particular period of day. If thecomparator 422 determines a dissimilarity measure indicating that theregularly activity is missing from the detected physical activitypattern at the particular period of day, it may indicate that thepatient is experiencing pain, which causes an absence of regularactivity. The operating mode control 242 may activate the second sensorcircuit 220, or acquire the data at a high data rate mode.

In addition to or in lieu of activation or deactivation of the secondsensor circuit 220, the operating mode control 242 may adjust dataacquisition rate of the second sensor circuit 220 based on thecomparison at the comparator 422, which may include, by way of exampleand not limitation, sampling rate, digitization resolution, or time andduration of data acquisition period. For example, if the comparison atthe comparator 422 indicates a decreased physical activity levelindicating a likelihood of pain onset or worsening pain, the operatingmode control 242 may control the second sensor circuit 220 to acquiredata at a higher sampling rate or a higher digitization resolution, orwith a longer data acquisition time period. This may help preserve theinformation of patient response to pain, and may improve pain assessmentaccuracy at the pain analyzer circuit 230. In an example, the secondsensor circuit 220 may remain active acquiring data, or remain in highsampling rate or high resolution mode until the physical activity levelstabilizes or exceeds a threshold indicating a pain relief orimprovement. If the comparison at the comparator 422 indicates a highphysical activity level, then the operating mode control 242 may reducethe sampling rate or the digitization resolution for the second sensorcircuit 220, or control the second sensor circuit 220 to acquire dataduring a shorter data acquisition period. The operating mode control 242may additionally or alternatively adjust data pre-processing of the dataacquired by the second sensor circuit 220 based on the physical activitylevel, such as adjusting one or more parameters of signal filtersincluding cutoff frequencies of a passband.

Operating mode of the second sensor as controlled by the physicalactivity level or other functional signals such as gait, balance,posture, range-of-motion, or sleep state may offer several benefits.Power and computing resources may be conserved by reducing the totalactivation time of second sensor, such as when the physical activity orother functional signals indicating a low likelihood of pain. The devicepower and computing resources may be reserved for sensor data collectionand analysis in case of an elevated likelihood of pain such as indicatedby reduced activity level. This may improve accuracy of painquantification at the pain analyzer circuit 230, while reduce theoverall operational cost of a pain management system such as anambulatory pain monitor.

In some examples, the operating mode control 242 may determine operatingmodes associated with different sensors further based on sensorsensitivity to physical activity. The second sensor circuit 220 mayacquire data from the different sensors according to their respectivelydetermined operating modes. For example, some sensors, such as heartsound sensor, are sensitive to physical activity and may be susceptibleto motion artifacts and other interferences during high activityperiods, and thus become less reliable for use in pain quantification.The second sensor circuit 220 may withhold data acquisition from thesesensors when a high activity level is detected at the first sensorcircuit 420. On the other hand, certain sensors, such as EMG sensor, maynot require a high sampling rate during periods of low activity (e.g.,during sleep), while some other sensors, such as PPG or galvanic skinresponse (GSR) sensor, are not sensitive to changes in physical activitylevel. The second sensor circuit 220, in response to a low physicalactivity detected at the first sensor circuit 420, may withhold dataacquisition or set a lower data acquisition rate for the EMG sensor, andset a high sampling rate for the PPG sensor or the GSR sensor.

The data sensed at the second sensor circuit 220 according to thedetermined operating mode may be used to assess pain at the painanalyzer circuit 230. In some examples, the extracted feature from thefeature extractor circuit 421, such as features of posture, gait,physical activity, balance, or range-of-motion, may also be used toassess pain and generate a pain score at the pain analyzer circuit 230.

FIG. 5 illustrates, by way of example and not limitation, a method 500for managing pain of a patient. The method 500 may be implemented in amedical system, such as the pain management system 200 or 300. In anexample, at least a portion of the method 500 may be executed by aneuromodulator device (iND) such as the implantable neuromodulator 310.In an example, at least a portion of the method 500 may be executed byan external programmer or remote server-based patient management system,such as the external system 320 that are communicatively coupled to theIND. The method 500 may be used to provide neuromodulation therapy totreat chronic pain or other disorders.

The method 500 begins at step 510, where a first signal indicative ofpatient functional state may be sensed from the patient. The functionalstate signal may include a motor activity signal. By way of example andnot limitation, motor activity signal may include patient posture, gait,balance, range-of-motion, or physical activity signals, among others. Insome examples, the functional state signal may include a sleep statesignal that contains information about sleep disturbance. Examples ofthe sleep state signals may include pain indicators during sleep, suchas frequency or duration of sleep position switch, sleep incline, orother indicators of sleep quality or change of sleep pattern. Chronicpain patients may present with poor or unbalanced posture, abnormal gaitpattern, restrained range-of-motion, or decreased intensity or durationof physical activities. Pain may also cause frequent sleep disturbanceand poor sleep quality. Monitoring patient motor control or sleepdisturbance may provide an objective assessment of pain, and may be usedto improve pain therapy efficacy. The functional signals may be sensedusing electrodes or ambulatory sensors, such as one or more motionsensors 411-415 associated with patient in different manners, asillustrated in FIG. 4.

At 520, an operating mode of a second sensor circuit may be determinedusing the received first signal. The second sensor circuit, such as thatillustrated in FIGS. 2 and 4, may be configured to sense a second signaldifferent from the first signal sensed at 510 under a specifiedoperating mode. The operating mode may include an activation ordeactivation of sensor data acquisition by the second sensor circuit, ordata sampling rate that the second sensor circuit uses for sampling thesecond signal. The operating mode may be determined using the controlcircuit 240 as illustrated in FIG. 2. The first signal sensed at 510 maybe compared to a specific criterion, such as a threshold or a valuerange, to determine whether to activate the data acquisition, time ofdata acquisition, or sampling rate of data acquisition of the secondsignal based on the comparison. Using the first sensor signal to triggeractivation and set operating mode of the second sensor may offer severalbenefits in pain management, particularly in ambulatory pain monitor andquantification. It may reduce power consumption and optimize devicememory usage. The functional state as indicated by the first sensedsignal may indicate a precursor of pain episode, and activation of dataacquisition and analysis of the second signal may generate a reliableconfirmation of pain episode or worsening of pain. Additionally, thefunctional signal may be used to prescreen the second sensor such as todetermine proper time for data acquisition to avoid interferences ornoise and thus allowing for a higher quality data for use in painassessment.

In an example, the operating mode of the second senor circuit may bedetermined using one or more functional signal features of the firstsignal, such as extracted by the feature extractor circuit 421. Examplesof the functional signal features may include physical activity featuressuch as activity intensity, activity duration, or a transition timebetween different types of activities; body position features duringsitting, standing, or walking; motor control and kinematic features suchas lumbar forward flexion, shoulder flexion, elbow flexion, rotation ofarm and elbow joint, trunk-pelvis rotation, or a rate or a pattern ofchange in motion with respect to time or with respect to angularvelocity; gait features such as time to peak velocity, step length,stride length, stride width, swing time, single limb support time,double limb stance, gait autonomy, cadence; or sleep state features suchas sleep incline, sleep sidedness, frequency of sleep position switch,or other sleep quality or sleep disturbance metrics, among other signalfeatures.

The extracted functional signal feature may be measured and trended overtime. In some examples, the functional signal features may be measuredduring a specified time period of daytime or nighttime, or in a specificcontext such as when the patient is asleep. The functional signalfeature trend may be compared to one or more thresholds or one or morevalue ranges to determine patient functional state. The operating modeof the second sensor circuit may be determined based on the patientfunctional state. In some examples, a physical activity pattern may bedetected, such as via the pattern detector 423, using measurements ofthe extracted feature over time. The detected physical activity patternmay be compared to a physical activity template representing a physicalactivity pattern under a known, controlled condition, such as a baselinepain-free condition. The operating mode of the second sensor circuit maybe determined based on the comparison between the detected physicalactivity pattern and the physical activity template.

At 530, a second signal different from the first signal may be sensed,such as via the second sensor circuit 220, under the operating mode asdetermined at 520. The second signal may include cardiac, pulmonary,neural, biochemical, or other physiological signals. Some of thesesignals may reveal characteristic signal properties in response to anonset, intensity, severity, duration, or patterns of pain. Examples ofthe second signal may include cardiac signals such as a heart ratesignal, a pulse rate signal, a heart rate variability signal,electrocardiograph (ECG) or intracardiac electrogram, cardiovascularpressure signal, or heart sounds signal, among others. The second signalmay additionally or alternatively include a galvanic skin response (GSR)signal, an electrodermal activity (EDA) signal, a skin temperaturesignal, an electromyogram (EMG) signal, an electroencephalogram (EEG)signal, a magnetoencephelogram (MEG) signal, a hemodynamic signal suchas a blood flow signal, a blood pressure signal, a blood perfusionsignal, a photoplethysmography (PPG) signal, or a saliva productionsignal indicating the change of amount of saliva production, amongothers.

In an example, the operating mode of the second sensor circuit may bedetermined at 520 using a physical activity signal. Physical activitylevel may indicate presence or severity of pain. Patient in pain aregenerally less active, such that periods of activity are generallyshorter and the activity intensity is generally lower. Therefore, a lowphysical activity level (in activity intensity or duration) may indicatea pain episode or precursor of pain has likely occurred, and a highphysical activity level may indicate that the patient is not likelyexperiencing pain. In some examples, the physical activity may bemeasured during a specified time period of daytime or nighttime, or in aspecific context such as when the patient is asleep. For example, a highphysical activity level during a period of nighttime or during sleep mayindicate onset of pain or undesirable pain treatment.

If the physical activity indicates that a pain episode or precursor ofpain has likely occurred, then at 530, the data acquisition of thesecond signal, such as a cardiac, pulmonary, muscular, or neurologicalsignal, may be initiated. Additionally, a higher data acquisition ratemay be used in response to the detection of the low physical activitylevel, including one or more of a higher sampling rate, a higherdigitization resolution, or a longer data acquisition time period, amongothers. This may preserve the information of patient response to pain,and thus improve the accuracy of pain quantification.

However, if the physical activity indicates that the patient is notlikely experiencing pain, then at 530, the data acquisition of thesecond signal may be withheld, or the sensor circuit for sensing thesecond signal may be at least temporarily deactivated. The operatingmode corresponding to the high physical activity level may additionallyor alternatively include a lower data acquisition rate, including one ormore of a lower sampling rate, a lower digitization resolution, or ashorter data acquisition time period, among others. When the physicalactivity or other functional signals indicate a low likelihood of pain,by reducing the activation time or acquiring data at lower data rate maysave power and computing resources. Power and computing resources may bereserved for sensor data collection and analysis in case of an elevatedlikelihood of pain such as indicated by reduced activity level.

In some examples, at 520, operating modes associated with differentsensors may be determined further based on a sensor's sensitivity tophysical activity. Some sensors, such as heart sound sensor, are moresensitive to physical activity and susceptible to motion artifacts andother interferences during high activity periods, and thus become lessreliable for use in pain quantification. On the other hand, certainsensors, such as EMG sensor, may not require a high sampling rate duringperiods of low activity (e.g., during sleep), while some other sensors,such as PPG or galvanic skin response (GSR) sensor, are not sensitive tochanges in physical activity level. At 530, sensor data may be acquiredfrom different sensors according to their respectively determinedoperating modes. For example, when a high activity level is detected,the sensors that are more susceptible to interferences and noises are atleast temporarily deactivated, the data acquisition from these sensorscan be withheld. When a low physical activity detected, data acquisitionof EMG may be withheld or set a lower data acquisition rate, and the PPGor the GSR signal may be acquired at a higher data acquisition rate.

At 540, a pain score may be generated using at least the second signalsensed under the determined operating mode, such as via the pain scoregenerator 232. The pain score may be generated using signal metricsgenerated from the second signal sensed under the determined operatingmode. The signal metrics may include statistical parameters,morphological parameters, or timing information such as a time intervalbetween a first characteristic point in one signal and a secondcharacteristic point in another signal. In an example, a compositesignal metric may be generated using a combination of a plurality of thesignal metrics respectively weighted by weight factors. The combinationcan be linear or nonlinear. The composite signal metric may becategorized as one of a number of degrees of pain by comparing thecomposite signal metric to one or more threshold values or range values,and a corresponding pain score may be assigned based on the comparison.In another example, the signal metrics may be compared to theirrespective threshold values or range values and a corresponding signalmetric-specific pain score may be determined. A composite pain score maybe generated using a linear or nonlinear fusion of the signalmetric-specific pain scores each weighted by their respective weightfactors. In some examples, the pain score may be computed using a subsetof the signal metrics selected based on their temporal profile of painresponse. Signal metrics with quick pain response (or a shortertransient state of response) may be selected to compute the pain scoreduring a pain episode. Signal metrics with slow or delayed pain response(or a longer transient state of response before reaching a steady state)may be used to compute the pain score after an extended period followingthe onset of pain such as to allow the signal metrics to reach steadystate of response. In some examples, patient demographic informationsuch as patient age or gender may be used in computing the pain score. Ahigher pain threshold for the composite signal metric may be selectedfor male patients than for female patients. Additionally oralternatively, the respective weight factors may be determined based onpatient demographic information. The weight factors for the signalmetrics may be tuned to a lower value than the weight factors for thesame signal metric in a female patient.

At 552, the pain score may be output to a user or to a process, such asvia the output circuit as illustrated in FIG. 2. The pain score,including the composite pain score and optionally together withmetric-specific pain scores, may be displayed on a display screen. Otherinformation such as the functional signals and the signal metricsextracted from the functional signals may also be output for display orfor further processing. In some examples, alerts, alarms, emergencycalls, or other forms of warnings may be generated to signal the systemuser about occurrence of a pain episode or aggravation of pain asindicated by the pain score.

The method 500 may include, at 554, an additional step of delivering apain therapy to the patient according to the pain score. The paintherapy may include electrostimulation therapy, such as spinal cordstimulation (SCS) via electrodes electrically coupled to theelectrostimulator. The SCS may be in a form of stimulation pulses thatare characterized by pulse amplitude, pulse width, stimulationfrequency, duration, on-off cycle, waveform, among other stimulationparameters. Other electrostimulation therapy, such as one or acombination of DBS, FES, VNS, TENS, or PNS at various locations, may bedelivered for pain management. The pain therapy may additionally oralternatively include a drug therapy such as delivered by using anintrathecal drug delivery pump.

In various examples, the pain therapy (such as in the form ofelectrostimulation or drug therapy) may be delivered in a closed-loopfashion. Therapy parameters, such as stimulation waveform parameters,stimulation electrode combination and fractionalization, drug dosage,may be adaptively adjusted based at least on the pain score. Thepain-relief effect of the delivered pain therapy may be assessed basedon the signal metrics such as the cardiovascular parameters, and thetherapy may be adjusted to achieve desirable pain relief. The therapyadjustment may be executed continuously, periodically at specific time,duration, or frequency, or in a commanded mode upon receiving from asystem user a command or confirmation of parameter adjustment. In anexample, if the pain score exceeds the pain threshold (or falls within aspecific range indicating an elevated pain), then the firstelectrostimulation may be delivered. Conversely, if the composite painscore falls below a respective threshold value (or falls within aspecific range indicating no pain or mild pain), then a second paintherapy, such as second electrostimulation may be delivered. The firstelectrostimulation may differ from the second electrostimulation withrespect to at least one of the stimulation energy, pulse amplitude,pulse width, stimulation frequency, duration, on-off cycle, pulse shapeor waveform, electrostimulation pattern such as electrode configurationor energy fractionalization among active electrodes, among otherstimulation parameters. In some examples, the responses of the signalmetrics to pain therapy delivered at 544 may be used to gauge compositepain score computation such as by adjusting the weight factors. In anexample, weight factors may be determined and adjusted via the weightgenerator 322 as illustrated in FIG. 3, to be proportional to signalmetric's sensitivity to pain.

FIG. 6 illustrates generally a block diagram of an example machine 600upon which any one or more of the techniques (e.g., methodologies)discussed herein may perform. Portions of this description may apply tothe computing framework of various portions of the LCP device, the IMD,or the external programmer.

In alternative embodiments, the machine 600 may operate as a standalonedevice or may be connected (e.g., networked) to other machines. In anetworked deployment, the machine 600 may operate in the capacity of aserver machine, a client machine, or both in server-client networkenvironments. In an example, the machine 600 may act as a peer machinein peer-to-peer (P2P) (or other distributed) network environment. Themachine 600 may be a personal computer (PC), a tablet PC, a set-top box(STB), a personal digital assistant (PDA), a mobile telephone, a webappliance, a network router, switch or bridge, or any machine capable ofexecuting instructions (sequential or otherwise) that specify actions tobe taken by that machine. Further, while only a single machine isillustrated, the term “machine” shall also be taken to include anycollection of machines that individually or jointly execute a set (ormultiple sets) of instructions to perform any one or more of themethodologies discussed herein, such as cloud computing, software as aservice (SaaS), other computer cluster configurations.

Examples, as described herein, may include, or may operate by, logic ora number of components, or mechanisms. Circuit sets are a collection ofcircuits implemented in tangible entities that include hardware (e.g.,simple circuits, gates, logic, etc.). Circuit set membership may beflexible over time and underlying hardware variability. Circuit setsinclude members that may, alone or in combination, perform specificoperations when operating. In an example, hardware of the circuit setmay be immutably designed to carry out a specific operation (e.g.,hardwired). In an example, the hardware of the circuit set may includevariably connected physical components (e.g., execution units,transistors, simple circuits, etc.) including a computer readable mediumphysically modified (e.g., magnetically, electrically, moveableplacement of invariant massed particles, etc.) to encode instructions ofthe specific operation. In connecting the physical components, theunderlying electrical properties of a hardware constituent are changed,for example, from an insulator to a conductor or vice versa. Theinstructions enable embedded hardware (e.g., the execution units or aloading mechanism) to create members of the circuit set in hardware viathe variable connections to carry out portions of the specific operationwhen in operation. Accordingly, the computer readable medium iscommunicatively coupled to the other components of the circuit setmember when the device is operating. In an example, any of the physicalcomponents may be used in more than one member of more than one circuitset. For example, under operation, execution units may be used in afirst circuit of a first circuit set at one point in time and reused bya second circuit in the first circuit set, or by a third circuit in asecond circuit set at a different time.

Machine (e.g., computer system) 600 may include a hardware processor 602(e.g., a central processing unit (CPU), a graphics processing unit(GPU), a hardware processor core, or any combination thereof), a mainmemory 604 and a static memory 606, some or all of which may communicatewith each other via an interlink (e.g., bus) 608. The machine 600 mayfurther include a display unit 610 (e.g., a raster display, vectordisplay, holographic display, etc.), an alphanumeric input device 612(e.g., a keyboard), and a user interface (UI) navigation device 614(e.g., a mouse). In an example, the display unit 610, input device 612and UI navigation device 614 may be a touch screen display. The machine600 may additionally include a storage device (e.g., drive unit) 616, asignal generation device 618 (e.g., a speaker), a network interfacedevice 620, and one or more sensors 621, such as a global positioningsystem (GPS) sensor, compass, accelerometer, or other sensor. Themachine 600 may include an output controller 628, such as a serial(e.g., universal serial bus (USB), parallel, or other wired or wireless(e.g., infrared (IR), near field communication (NFC), etc.) connectionto communicate or control one or more peripheral devices (e.g., aprinter, card reader, etc.).

The storage device 616 may include a machine readable medium 622 onwhich is stored one or more sets of data structures or instructions 624(e.g., software) embodying or utilized by any one or more of thetechniques or functions described herein. The instructions 624 may alsoreside, completely or at least partially, within the main memory 604,within static memory 606, or within the hardware processor 602 duringexecution thereof by the machine 600. In an example, one or anycombination of the hardware processor 602, the main memory 604, thestatic memory 606, or the storage device 616 may constitute machinereadable media.

While the machine readable medium 622 is illustrated as a single medium,the term “machine readable medium” may include a single medium ormultiple media (e.g., a centralized or distributed database, and/orassociated caches and servers) configured to store the one or moreinstructions 624.

The term “machine readable medium” may include any medium that iscapable of storing, encoding, or carrying instructions for execution bythe machine 600 and that cause the machine 600 to perform any one ormore of the techniques of the present disclosure, or that is capable ofstoring, encoding or carrying data structures used by or associated withsuch instructions. Non-limiting machine readable medium examples mayinclude solid-state memories, and optical and magnetic media. In anexample, a massed machine readable medium comprises a machine readablemedium with a plurality of particles having invariant (e.g., rest) mass.Accordingly, massed machine-readable media are not transitorypropagating signals. Specific examples of massed machine readable mediamay include: non-volatile memory, such as semiconductor memory devices(e.g., Electrically Programmable Read-Only Memory (EPROM), ElectricallyErasable Programmable Read-Only Memory (EEPROM)) and flash memorydevices; magnetic disks, such as internal hard disks and removabledisks; magneto-optical disks; and CD-ROM and DVD-ROM disks.

The instructions 624 may further be transmitted or received over acommunications network 626 using a transmission medium via the networkinterface device 620 utilizing any one of a number of transfer protocols(e.g., frame relay, internet protocol (IP), transmission controlprotocol (TCP), user datagram protocol (UDP), hypertext transferprotocol (HTTP), etc.). Example communication networks may include alocal area network (LAN), a wide area network (WAN), a packet datanetwork (e.g., the Tnternet), mobile telephone networks (e.g., cellularnetworks), Plain Old Telephone (POTS) networks, and wireless datanetworks (e.g., Institute of Electrical and Electronics Engineers (IEEE)802.11 family of standards known as WiFi®, IEEE 802.16 family ofstandards known as WiMax®), IEEE 802.15.4 family of standards,peer-to-peer (P2P) networks, among others. In an example, the networkinterface device 620 may include one or more physical jacks (e.g.,Ethernet, coaxial, or phone jacks) or one or more antennas to connect tothe communications network 626. In an example, the network interfacedevice 620 may include a plurality of antennas to wirelessly communicateusing at least one of single-input multiple-output (SIMO),multiple-input multiple-output (MIMO), or multiple-input single-output(MISO) techniques. The term “transmission medium” shall be taken toinclude any intangible medium that is capable of storing, encoding orcarrying instructions for execution by the machine 600, and includesdigital or analog communications signals or other intangible medium tofacilitate communication of such software.

Various embodiments are illustrated in the figures above. One or morefeatures from one or more of these embodiments may be combined to formother embodiments.

The method examples described herein can be machine orcomputer-implemented at least in part. Some examples may include acomputer-readable medium or machine-readable medium encoded withinstructions operable to configure an electronic device or system toperform methods as described in the above examples. An implementation ofsuch methods may include code, such as microcode, assembly languagecode, a higher-level language code, or the like. Such code may includecomputer readable instructions for performing various methods. The codecan form portions of computer program products. Further, the code can betangibly stored on one or more volatile or non-volatilecomputer-readable media during execution or at other times.

The above detailed description is intended to be illustrative, and notrestrictive. The scope of the disclosure should, therefore, bedetermined with references to the appended claims, along with the fullscope of equivalents to which such claims are entitled.

What is claimed is:
 1. A system comprising: a sensor circuit configuredto sense a physiological signal from a patient; and a controller circuitconfigured to: receive information about a functional state of thepatient; determine an operating mode of the sensor circuit based on thereceived information about the functional state of the patient; activatethe sensor circuit to sense the physiological signal under thedetermined operating mode in response to the received information aboutthe functional state satisfying a condition; and generate a controlsignal to initiate or adjust an electrostimulation therapy to thepatient based on the sensed physiological signal.
 2. The system of claim1, wherein the controller circuit is configured to determine theoperating mode of the sensor circuit including adjusting a sampling ratefor sensing the physiological signal.
 3. The system of claim 1, whereinthe controller circuit is configured to determine the operating mode ofthe sensor circuit including adjusting time or duration for sensing thephysiological signal.
 4. The system of claim 1, wherein the receivedinformation about the functional state of the patient includes at leastone of: a physical activity parameter; a posture; a range of motion; agait; a balance; or a sleep state.
 5. The system of claim 4, wherein thereceived information about the functional state includes a physicalactivity parameter, and wherein the controller circuit is configured toactivate the sensor circuit to sense the physiological signal under thedetermined operating mode when the physical activity parameter fallsbelow an activity level threshold.
 6. The system of claim 5, wherein thephysical activity parameter is measured during nighttime or when thepatient is asleep.
 7. The system of claim 1, wherein the controllercircuit is configured to activate the sensor circuit to sense thephysiological signal including at least one of: a cardiac electricalactivity signal; an electromyography signal; a photoplethysmographysignal; a galvanic skin response signal; an electroencephalogram signal;or a hemodynamic signal.
 8. The system of claim 1, comprising animplantable neuromodulator device configured to deliver theelectrostimulation therapy to the patient based on the sensedphysiological signal, wherein the implantable neuromodulator deviceincludes the control circuit and is configured to be communicativelycoupled to an external device configured to sense the information aboutthe functional state of the patient.
 9. The system of claim 8, whereinthe external device is a wearable mobile device.
 10. The system of claim8, wherein the implantable neuromodulator device is configured todeliver deep brain stimulation to the patient in response to the sensedphysiological signal satisfying a condition.
 11. The system of claim 1,wherein: the sensor circuit is configured to sense the physiologicalsignal in response to delivering electrostimulation to the patient; andthe controller circuit is configured to determine an electrostimulationparameter based on the sensed physiological signal in response to theelectrostimulation, and to generate the control signal to adjust theelectrostimulation therapy in accordance with the determinedelectrostimulation parameter.
 12. A method of operating a neuromodulatordevice to provide neuromodulation therapy to a patient, the methodcomprising: receiving information about a functional state of thepatient; determining an operating mode of a sensor circuit based on thereceived information about the functional state of the patient;activating the sensor circuit to sense a physiological signal under thedetermined operating mode in response to the received information aboutthe functional state satisfying a condition; and delivering anelectrostimulation therapy to the patient based on the sensedphysiological signal.
 13. The method of claim 12, wherein determiningthe operating mode of the sensor circuit includes determining at leastone of a sampling rate, timing, or duration for sensing thephysiological signal based on the received information about thefunctional state of the patient.
 14. The method of claim 12, wherein thedelivering the electrostimulation therapy includes delivering deep brainstimulation to the patient in response to the sensed physiologicalsignal satisfying a condition.
 15. The method of claim 12, whereinactivating the sensor circuit to sense the physiological signal is inresponse to delivering electrostimulation to the patient, and the methodfurther comprises adjusting an electrostimulation parameter based on thesensed physiological signal, wherein delivering the electrostimulationtherapy is in accordance with the adjusted electrostimulation parameter.16. A non-transitory machine-readable storage medium that includesinstructions that, when executed by one or more processors of a machine,cause the machine to perform operations comprising: receivinginformation about a functional state of the patient; determining anoperating mode of a sensor circuit based on the received informationabout the functional state of the patient; activating the sensor circuitto sense a physiological signal under the determined operating mode inresponse to the received information about the functional statesatisfying a condition; and delivering an electrostimulation therapy tothe patient based on the sensed physiological signal.
 17. Thenon-transitory machine-readable storage medium of claim 16, wherein theoperation of determining the operating mode of the sensor circuitincludes determining at least one of a sampling rate, a timing, or aduration for sensing the physiological signal based on the receivedinformation about the functional state of the patient.
 18. Thenon-transitory machine-readable storage medium of claim 16, wherein theinstructions cause the machine to perform operations further comprisingcommunicating with an external device and receiving therefrom theinformation about the functional state of the patient.
 19. Thenon-transitory machine-readable storage medium of claim 16, wherein theoperation of delivering the electrostimulation therapy includesdelivering deep brain stimulation to the patient in response to thesensed physiological signal satisfying a condition.
 20. Thenon-transitory machine-readable storage medium of claim 16, wherein theoperation of activating the sensor circuit to sense the physiologicalsignal is in response to delivering electrostimulation to the patient,and wherein the instructions cause the machine to perform operationsfurther comprising: adjusting an electrostimulation parameter based onthe sensed physiological signal; and delivering the electrostimulationtherapy in accordance with the adjusted electrostimulation parameter.